Estimating the Location of Brodmann Areas from Cortical Folding Patterns Using Histology and Ex Vivo MRI

Abstract

The human cerebral cortex can be parcellated into a mosaic of microscopically (i.e., architectonically) definable areas based on localizable and more or less pronounced changes in the laminar distribution of neuronal cell bodies (cytoarchitecture) and/or intracortical myelinated fibers (myeloarchitecture) (Brodmann K (1909) Vergleichende Lokalisationslehre der Groshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Verlag von Johann Ambrosius Barth, Leipzig; Vogt (J Psychol Neurol 18:107–118, 1911); von Economo C (1929) The cytoarchitectonics of the human cerebral cortex. Oxford University Press, London; Sarkissov S, Filimonoff I, Kononova IP, Preobrazenskaja NS, Kukueva L (1955) Atlas of the cytoarchitectonics of the human cerebral cortex. Medgiz, Moscov). The most famous of these parcellations is the one proposed by Korbinian Brodmann (1909) Vergleichende Lokalisationslehre der Groshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Verlag von Johann Ambrosius Barth, Leipzig) a century ago. Most current imaging studies of the human cortex report the location of effects as a “Brodmann area” (BA). Although these attributions are common, they are not typically accompanied by any rigorous statistical analysis of the uncertainty associated with the localization. More commonly researchers identify Brodmann areas based on an ad hoc assessment of the location of interest relative to surrounding folding patterns. This approach is problematic as (1) there is no means to rigorously test the uncertainty of the localizations, and (2) until recently, little has been known about the relationship between the Brodmann areas and the cortical folds. In this chapter, I discuss methods for using imaging and computational tools to more accurately localize Brodmann areas, as well as to quantify the uncertainty associated with the localization. This includes the use of ultra-high-resolution ex vivo MRI, the geometry of cortical folding patterns, and the minimum interior distance that axonal fibers would need to traverse in order to connect two cortical areas. The results both improve state-of-the-art accuracy in the in vivo estimation of architectonic boundaries, but also provide some insight into the relationship between the variability of areal boundaries with respect to cortical folding patterns and an area’s place in a putative cortical processing hierarchy.